anova() tests if some fixed effects can be dropped.
Uses Chi-sq-test for likelihood-ratio instead of F-test for residuals
Fit models with REML=FALSE !
lmm1 = lmer( flipper_length_mm ~ mass_z * species + (1|sex), data=data, REML=FALSE )
lmm2 = lmer( flipper_length_mm ~ mass_z + species + (1|sex), data=data, REML=FALSE )
anova(lmm1, lmm2)
## Data: data
## Models:
## lmm2: flipper_length_mm ~ mass_z + species + (1 | sex)
## lmm1: flipper_length_mm ~ mass_z * species + (1 | sex)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## lmm2 6 2074.5 2097.3 -1031.2 2062.5
## lmm1 8 2069.3 2099.7 -1026.6 2053.3 9.2154 2 0.009975 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
H0: Models perform equally well.
\(P<0.05\) âž” Keep full model.